BLIP-2

BLIP-2 (Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models) is a recent Visual Language Model (VLM) that achieves strong performance on various multimodal tasks by effectively integrating pre-trained vision and language models. BLIP-2 introduces a novel approach to connect visual features from a frozen image encoder to a large language model (LLM) using lightweight Q-Former modules. This design allows BLIP-2 to leverage the strengths of both vision and language models without requiring extensive fine-tuning of the entire architecture.